Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC

Authored by Mustafa Lokhandwala, Hua Cai

Date Published: 2018

DOI: 10.1016/j.trc.2018.10.007

Sponsors: No sponsors listed

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Model Documentation: Other Narrative Flow charts Pseudocode

Model Code URLs: Model code not found

Abstract

This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional taxis (with shifts) and shared autonomous taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional taxis to autonomous taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional taxis to shared autonomous taxis can potentially reduce the fleet size by 59\% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55\%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50-75\% level. However, the reduced fleet from ride sharing and autonomous driving may cause taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.

Tags

Agent-based model Simulation Life-cycle assessment Choice Agent-based model Vehicle Benefits Ride sharing Shared autonomous vehicles Taxi sharing Travel-times